Comparison between neural networks and partial least squares for intra-growth ring wood density measurement with hyperspectral imaging.

Highlights: [•] Hyperspectral imaging allows measuring wood density at 79μm spatial resolution. [•] Partial least squares or neural networks transform hyperspectral data to density. [•] Neural networks provide better results than partial least squares. [•] The mean absolute percentage error for neural networks is 6.49%. [•] Our method may substitute X-ray microdensitometry measurements. [Copyright &y& Elsevier]